# Django 2.0.dev20170216164632 documentation

# Database Functions

The classes documented below provide a way for users to use functions provided by the underlying database as annotations, aggregations, or filters in Django. Functions are also expressions, so they can be used and combined with other expressions like aggregate functions.

We’ll be using the following model in examples of each function:

    class Author(models.Model):
        name = models.CharField(max_length=50)
        age = models.PositiveIntegerField(null=True, blank=True)
        alias = models.CharField(max_length=50, null=True, blank=True)
        goes_by = models.CharField(max_length=50, null=True, blank=True)

We don’t usually recommend allowing `null=True` for `CharField` since this allows the field to have two “empty values”, but it’s important for the `Coalesce` example below.

## `Cast`

class `Cast`(expression, output_field)

Forces the result type of `expression` to be the one from `output_field`.

Usage example:

    >>> from django.db.models import FloatField
    >>> from django.db.models.functions import Cast
    >>> Value.objects.create(integer=4)
    >>> value = Value.objects.annotate(as_float=Cast('integer', FloatField())).get()
    >>> print(value.as_float)
    4.0

## `Coalesce`

class `Coalesce`(*expressions, **extra)

Accepts a list of at least two field names or expressions and returns the first non-null value (note that an empty string is not considered a null value). Each argument must be of a similar type, so mixing text and numbers will result in a database error.

Usage examples:

    >>> # Get a screen name from least to most public
    >>> from django.db.models import Sum, Value as V
    >>> from django.db.models.functions import Coalesce
    >>> Author.objects.create(name='Margaret Smith', goes_by='Maggie')
    >>> author = Author.objects.annotate(
    ...    screen_name=Coalesce('alias', 'goes_by', 'name')).get()
    >>> print(author.screen_name)
    Maggie

    >>> # Prevent an aggregate Sum() from returning None
    >>> aggregated = Author.objects.aggregate(
    ...    combined_age=Coalesce(Sum('age'), V(0)),
    ...    combined_age_default=Sum('age'))
    >>> print(aggregated['combined_age'])
    0
    >>> print(aggregated['combined_age_default'])
    None

Warning

A Python value passed to `Coalesce` on MySQL may be converted to an incorrect type unless explicitly cast to the correct database type:

    >>> from django.db.models import DateTimeField
    >>> from django.db.models.functions import Cast, Coalesce
    >>> from django.utils import timezone
    >>> now = timezone.now()
    >>> Coalesce('updated', Cast(now, DateTimeField()))

## `Concat`

class `Concat`(*expressions, **extra)

Accepts a list of at least two text fields or expressions and returns the concatenated text. Each argument must be of a text or char type. If you want to concatenate a `TextField()` with a `CharField()`, then be sure to tell Django that the `output_field` should be a `TextField()`. This is also required when concatenating a `Value` as in the example below.

This function will never have a null result. On backends where a null argument results in the entire expression being null, Django will ensure that each null part is converted to an empty string first.

Usage example:

    >>> # Get the display name as "name (goes_by)"
    >>> from django.db.models import CharField, Value as V
    >>> from django.db.models.functions import Concat
    >>> Author.objects.create(name='Margaret Smith', goes_by='Maggie')
    >>> author = Author.objects.annotate(
    ...    screen_name=Concat('name', V(' ('), 'goes_by', V(')'),
    ...    output_field=CharField())).get()
    >>> print(author.screen_name)
    Margaret Smith (Maggie)

## `Greatest`

class `Greatest`(*expressions, **extra)

Accepts a list of at least two field names or expressions and returns the greatest value. Each argument must be of a similar type, so mixing text and numbers will result in a database error.

Usage example:

    class Blog(models.Model):
        body = models.TextField()
        modified = models.DateTimeField(auto_now=True)

    class Comment(models.Model):
        body = models.TextField()
        modified = models.DateTimeField(auto_now=True)
        blog = models.ForeignKey(Blog, on_delete=models.CASCADE)

    >>> from django.db.models.functions import Greatest
    >>> blog = Blog.objects.create(body='Greatest is the best.')
    >>> comment = Comment.objects.create(body='No, Least is better.', blog=blog)
    >>> comments = Comment.objects.annotate(last_updated=Greatest('modified', 'blog__modified'))
    >>> annotated_comment = comments.get()

`annotated_comment.last_updated` will be the most recent of `blog.modified` and `comment.modified`.

Warning

The behavior of `Greatest` when one or more expression may be `null` varies between databases:

- PostgreSQL: `Greatest` will return the largest non-null expression, or `null` if all expressions are `null`.
- SQLite, Oracle, and MySQL: If any expression is `null`, `Greatest` will return `null`.

The PostgreSQL behavior can be emulated using `Coalesce` if you know a sensible minimum value to provide as a default.

## `Least`

class `Least`(*expressions, **extra)

Accepts a list of at least two field names or expressions and returns the least value. Each argument must be of a similar type, so mixing text and numbers will result in a database error.

Warning

The behavior of `Least` when one or more expression may be `null` varies between databases:

- PostgreSQL: `Least` will return the smallest non-null expression, or `null` if all expressions are `null`.
- SQLite, Oracle, and MySQL: If any expression is `null`, `Least` will return `null`.

The PostgreSQL behavior can be emulated using `Coalesce` if you know a sensible maximum value to provide as a default.

## `Length`

class `Length`(expression, **extra)

Accepts a single text field or expression and returns the number of characters the value has. If the expression is null, then the length will also be null.

Usage example:

    >>> # Get the length of the name and goes_by fields
    >>> from django.db.models.functions import Length
    >>> Author.objects.create(name='Margaret Smith')
    >>> author = Author.objects.annotate(
    ...    name_length=Length('name'),
    ...    goes_by_length=Length('goes_by')).get()
    >>> print(author.name_length, author.goes_by_length)
    (14, None)

It can also be registered as a transform. For example:

    >>> from django.db.models import CharField
    >>> from django.db.models.functions import Length
    >>> CharField.register_lookup(Length, 'length')
    >>> # Get authors whose name is longer than 7 characters
    >>> authors = Author.objects.filter(name__length__gt=7)

## `Lower`

class `Lower`(expression, **extra)

Accepts a single text field or expression and returns the lowercase representation.

It can also be registered as a transform as described in `Length`.

Usage example:

    >>> from django.db.models.functions import Lower
    >>> Author.objects.create(name='Margaret Smith')
    >>> author = Author.objects.annotate(name_lower=Lower('name')).get()
    >>> print(author.name_lower)
    margaret smith

## `Now`

class `Now`

Returns the database server’s current date and time when the query is executed, typically using the SQL `CURRENT_TIMESTAMP`.

Usage example:

    >>> from django.db.models.functions import Now
    >>> Article.objects.filter(published__lte=Now())
    <QuerySet [<Article: How to Django>]>

PostgreSQL considerations

On PostgreSQL, the SQL `CURRENT_TIMESTAMP` returns the time that the current transaction started. Therefore for cross-database compatibility, `Now()` uses `STATEMENT_TIMESTAMP` instead. If you need the transaction timestamp, use `django.contrib.postgres.functions.TransactionNow`.

## `Substr`

class `Substr`(expression, pos, length=None, **extra)

Returns a substring of length `length` from the field or expression starting at position `pos`. The position is 1-indexed, so the position must be greater than 0. If `length` is `None`, then the rest of the string will be returned.

Usage example:

    >>> # Set the alias to the first 5 characters of the name as lowercase
    >>> from django.db.models.functions import Substr, Lower
    >>> Author.objects.create(name='Margaret Smith')
    >>> Author.objects.update(alias=Lower(Substr('name', 1, 5)))
    1
    >>> print(Author.objects.get(name='Margaret Smith').alias)
    marga

## `Upper`

class `Upper`(expression, **extra)

Accepts a single text field or expression and returns the uppercase representation.

It can also be registered as a transform as described in `Length`.

Usage example:

    >>> from django.db.models.functions import Upper
    >>> Author.objects.create(name='Margaret Smith')
    >>> author = Author.objects.annotate(name_upper=Upper('name')).get()
    >>> print(author.name_upper)
    MARGARET SMITH

## Date Functions

We’ll be using the following model in examples of each function:

    class Experiment(models.Model):
        start_datetime = models.DateTimeField()
        start_date = models.DateField(null=True, blank=True)
        start_time = models.TimeField(null=True, blank=True)
        end_datetime = models.DateTimeField(null=True, blank=True)
        end_date = models.DateField(null=True, blank=True)
        end_time = models.TimeField(null=True, blank=True)

### `Extract`

class `Extract`(expression, lookup_name=None, tzinfo=None, **extra)

Extracts a component of a date as a number.

Takes an `expression` representing a `DateField` or `DateTimeField` and a `lookup_name`, and returns the part of the date referenced by `lookup_name` as an `IntegerField`. Django usually uses the databases’ extract function, so you may use any `lookup_name` that your database supports. A `tzinfo` subclass, usually provided by `pytz`, can be passed to extract a value in a specific timezone.

Given the datetime `2015-06-15 23:30:01.000321+00:00`, the built-in `lookup_name`s return:

- “year”: 2015
- “month”: 6
- “day”: 15
- “week”: 25
- “week_day”: 2
- “hour”: 23
- “minute”: 30
- “second”: 1

If a different timezone like `Australia/Melbourne` is active in Django, then the datetime is converted to the timezone before the value is extracted. The timezone offset for Melbourne in the example date above is +10:00. The values returned when this timezone is active will be the same as above except for:

- “day”: 16
- “week_day”: 3
- “hour”: 9

`week_day` values

The `week_day` `lookup_type` is calculated differently from most databases and from Python’s standard functions. This function will return `1` for Sunday, `2` for Monday, through `7` for Saturday.

The equivalent calculation in Python is:

    >>> from datetime import datetime
    >>> dt = datetime(2015, 6, 15)
    >>> (dt.isoweekday() % 7) + 1
    2

`week` values

The `week` `lookup_type` is calculated based on ISO-8601, i.e., a week starts on a Monday. The first week is the one with the majority of the days, i.e., a week that starts on or before Thursday. The value returned is in the range 1 to 52 or 53.

Each `lookup_name` above has a corresponding `Extract` subclass (listed below) that should typically be used instead of the more verbose equivalent, e.g. use `ExtractYear(...)` rather than `Extract(..., lookup_name='year')`.

Usage example:

    >>> from datetime import datetime
    >>> from django.db.models.functions import Extract
    >>> start = datetime(2015, 6, 15)
    >>> end = datetime(2015, 7, 2)
    >>> Experiment.objects.create(
    ...    start_datetime=start, start_date=start.date(),
    ...    end_datetime=end, end_date=end.date())
    >>> # Add the experiment start year as a field in the QuerySet.
    >>> experiment = Experiment.objects.annotate(
    ...    start_year=Extract('start_datetime', 'year')).get()
    >>> experiment.start_year
    2015
    >>> # How many experiments completed in the same year in which they started?
    >>> Experiment.objects.filter(
    ...    start_datetime__year=Extract('end_datetime', 'year')).count()
    1

#### `DateField` extracts

class `ExtractYear`(expression, tzinfo=None, **extra)
  `lookup_name = 'year'`

class `ExtractMonth`(expression, tzinfo=None, **extra)
  `lookup_name = 'month'`

class `ExtractDay`(expression, tzinfo=None, **extra)
  `lookup_name = 'day'`

class `ExtractWeekDay`(expression, tzinfo=None, **extra)
  `lookup_name = 'week_day'`

class `ExtractWeek`(expression, tzinfo=None, **extra)
  `lookup_name = 'week'`

These are logically equivalent to `Extract('date_field', lookup_name)`. Each class is also a `Transform` registered on `DateField` and `DateTimeField` as `__(lookup_name)`, e.g. `__year`.

Since `DateField`s don’t have a time component, only `Extract` subclasses that deal with date-parts can be used with `DateField`:

    >>> from datetime import datetime
    >>> from django.utils import timezone
    >>> from django.db.models.functions import (
    ...    ExtractYear, ExtractMonth, ExtractDay, ExtractWeekDay
    ... )
    >>> start_2015 = datetime(2015, 6, 15, 23, 30, 1, tzinfo=timezone.utc)
    >>> end_2015 = datetime(2015, 6, 16, 13, 11, 27, tzinfo=timezone.utc)
    >>> Experiment.objects.create(
    ...    start_datetime=start_2015, start_date=start_2015.date(),
    ...    end_datetime=end_2015, end_date=end_2015.date())
    >>> Experiment.objects.annotate(
    ...     year=ExtractYear('start_date'),
    ...     month=ExtractMonth('start_date'),
    ...     day=ExtractDay('start_date'),
    ...     weekday=ExtractWeekDay('start_date'),
    ... ).values('year', 'month', 'day', 'weekday').get(
    ...     end_date__year=ExtractYear('start_date'),
    ... )
    {'year': 2015, 'month': 6, 'day': 15, 'weekday': 2}

#### `DateTimeField` extracts

In addition to the following, all extracts for `DateField` listed above may also be used on `DateTimeField`s .

class `ExtractHour`(expression, tzinfo=None, **extra)
  `lookup_name = 'hour'`

class `ExtractMinute`(expression, tzinfo=None, **extra)
  `lookup_name = 'minute'`

class `ExtractSecond`(expression, tzinfo=None, **extra)
  `lookup_name = 'second'`

These are logically equivalent to `Extract('datetime_field', lookup_name)`. Each class is also a `Transform` registered on `DateTimeField` as `__(lookup_name)`, e.g. `__minute`.

`DateTimeField` examples:

    >>> from datetime import datetime
    >>> from django.utils import timezone
    >>> from django.db.models.functions import (
    ...    ExtractYear, ExtractMonth, ExtractDay, ExtractWeekDay,
    ...    ExtractHour, ExtractMinute, ExtractSecond,
    ... )
    >>> start_2015 = datetime(2015, 6, 15, 23, 30, 1, tzinfo=timezone.utc)
    >>> end_2015 = datetime(2015, 6, 16, 13, 11, 27, tzinfo=timezone.utc)
    >>> Experiment.objects.create(
    ...    start_datetime=start_2015, start_date=start_2015.date(),
    ...    end_datetime=end_2015, end_date=end_2015.date())
    >>> Experiment.objects.annotate(
    ...     year=ExtractYear('start_datetime'),
    ...     month=ExtractMonth('start_datetime'),
    ...     day=ExtractDay('start_datetime'),
    ...     weekday=ExtractWeekDay('start_datetime'),
    ...     hour=ExtractHour('start_datetime'),
    ...     minute=ExtractMinute('start_datetime'),
    ...     second=ExtractSecond('start_datetime'),
    ... ).values(
    ...     'year', 'month', 'day', 'weekday', 'hour', 'minute', 'second',
    ... ).get(end_datetime__year=ExtractYear('start_datetime'))
    {'year': 2015, 'month': 6, 'day': 15, 'weekday': 2, 'hour': 23, 'minute': 30, 'second': 1}

When `USE_TZ` is `True` then datetimes are stored in the database in UTC. If a different timezone is active in Django, the datetime is converted to that timezone before the value is extracted. The example below converts to the Melbourne timezone (UTC +10:00), which changes the day, weekday, and hour values that are returned:

    >>> import pytz
    >>> tzinfo = pytz.timezone('Australia/Melbourne')  # UTC+10:00
    >>> with timezone.override(tzinfo):
    ...    Experiment.objects.annotate(
    ...        day=ExtractDay('start_datetime'),
    ...        weekday=ExtractWeekDay('start_datetime'),
    ...        hour=ExtractHour('start_datetime'),
    ...    ).values('day', 'weekday', 'hour').get(
    ...        end_datetime__year=ExtractYear('start_datetime'),
    ...    )
    {'day': 16, 'weekday': 3, 'hour': 9}

Explicitly passing the timezone to the `Extract` function behaves in the same way, and takes priority over an active timezone:

    >>> import pytz
    >>> tzinfo = pytz.timezone('Australia/Melbourne')
    >>> Experiment.objects.annotate(
    ...     day=ExtractDay('start_datetime', tzinfo=melb),
    ...     weekday=ExtractWeekDay('start_datetime', tzinfo=melb),
    ...     hour=ExtractHour('start_datetime', tzinfo=melb),
    ... ).values('day', 'weekday', 'hour').get(
    ...     end_datetime__year=ExtractYear('start_datetime'),
    ... )
    {'day': 16, 'weekday': 3, 'hour': 9}

### `Trunc`

class `Trunc`(expression, kind, output_field=None, tzinfo=None, **extra)

Truncates a date up to a significant component.

When you only care if something happened in a particular year, hour, or day, but not the exact second, then `Trunc` (and its subclasses) can be useful to filter or aggregate your data. For example, you can use `Trunc` to calculate the number of sales per day.

`Trunc` takes a single `expression`, representing a `DateField`, `TimeField`, or `DateTimeField`, a `kind` representing a date or time part, and an `output_field` that’s either `DateTimeField()`, `TimeField()`, or `DateField()`. It returns a datetime, date, or time depending on `output_field`, with fields up to `kind` set to their minimum value. If `output_field` is omitted, it will default to the `output_field` of `expression`. A `tzinfo` subclass, usually provided by `pytz`, can be passed to truncate a value in a specific timezone.

Given the datetime `2015-06-15 14:30:50.000321+00:00`, the built-in `kind`s return:

- “year”: 2015-01-01 00:00:00+00:00
- “month”: 2015-06-01 00:00:00+00:00
- “day”: 2015-06-15 00:00:00+00:00
- “hour”: 2015-06-15 14:00:00+00:00
- “minute”: 2015-06-15 14:30:00+00:00
- “second”: 2015-06-15 14:30:50+00:00

If a different timezone like `Australia/Melbourne` is active in Django, then the datetime is converted to the new timezone before the value is truncated. The timezone offset for Melbourne in the example date above is +10:00. The values returned when this timezone is active will be:

- “year”: 2015-01-01 00:00:00+11:00
- “month”: 2015-06-01 00:00:00+10:00
- “day”: 2015-06-16 00:00:00+10:00
- “hour”: 2015-06-16 00:00:00+10:00
- “minute”: 2015-06-16 00:30:00+10:00
- “second”: 2015-06-16 00:30:50+10:00

The year has an offset of +11:00 because the result transitioned into daylight saving time.

Each `kind` above has a corresponding `Trunc` subclass (listed below) that should typically be used instead of the more verbose equivalent, e.g. use `TruncYear(...)` rather than `Trunc(..., kind='year')`.

The subclasses are all defined as transforms, but they aren’t registered with any fields, because the obvious lookup names are already reserved by the `Extract` subclasses.

Usage example:

    >>> from datetime import datetime
    >>> from django.db.models import Count, DateTimeField
    >>> from django.db.models.functions import Trunc
    >>> Experiment.objects.create(start_datetime=datetime(2015, 6, 15, 14, 30, 50, 321))
    >>> Experiment.objects.create(start_datetime=datetime(2015, 6, 15, 14, 40, 2, 123))
    >>> Experiment.objects.create(start_datetime=datetime(2015, 12, 25, 10, 5, 27, 999))
    >>> experiments_per_day = Experiment.objects.annotate(
    ...    start_day=Trunc('start_datetime', 'day', output_field=DateTimeField())
    ... ).values('start_day').annotate(experiments=Count('id'))
    >>> for exp in experiments_per_day:
    ...     print(exp['start_day'], exp['experiments'])
    ...
    2015-06-15 00:00:00 2
    2015-12-25 00:00:00 1
    >>> experiments = Experiment.objects.annotate(
    ...    start_day=Trunc('start_datetime', 'day', output_field=DateTimeField())
    ... ).filter(start_day=datetime(2015, 6, 15))
    >>> for exp in experiments:
    ...     print(exp.start_datetime)
    ...
    2015-06-15 14:30:50.000321
    2015-06-15 14:40:02.000123

#### `DateField` truncation

class `TruncYear`(expression, output_field=None, tzinfo=None, **extra)
  `kind = 'year'`

class `TruncMonth`(expression, output_field=None, tzinfo=None, **extra)
  `kind = 'month'`

These are logically equivalent to `Trunc('date_field', kind)`. They truncate all parts of the date up to `kind` which allows grouping or filtering dates with less precision. `expression` can have an `output_field` of either `DateField` or `DateTimeField`.

Since `DateField`s don’t have a time component, only `Trunc` subclasses that deal with date-parts can be used with `DateField`:

    >>> from datetime import datetime
    >>> from django.db.models import Count
    >>> from django.db.models.functions import TruncMonth, TruncYear
    >>> from django.utils import timezone
    >>> start1 = datetime(2014, 6, 15, 14, 30, 50, 321, tzinfo=timezone.utc)
    >>> start2 = datetime(2015, 6, 15, 14, 40, 2, 123, tzinfo=timezone.utc)
    >>> start3 = datetime(2015, 12, 31, 17, 5, 27, 999, tzinfo=timezone.utc)
    >>> Experiment.objects.create(start_datetime=start1, start_date=start1.date())
    >>> Experiment.objects.create(start_datetime=start2, start_date=start2.date())
    >>> Experiment.objects.create(start_datetime=start3, start_date=start3.date())
    >>> experiments_per_year = Experiment.objects.annotate(
    ...    year=TruncYear('start_date')).values('year').annotate(
    ...    experiments=Count('id'))
    >>> for exp in experiments_per_year:
    ...     print(exp['year'], exp['experiments'])
    ...
    2014-01-01 1
    2015-01-01 2

    >>> import pytz
    >>> melb = pytz.timezone('Australia/Melbourne')
    >>> experiments_per_month = Experiment.objects.annotate(
    ...    month=TruncMonth('start_datetime', tzinfo=melb)).values('month').annotate(
    ...    experiments=Count('id'))
    >>> for exp in experiments_per_month:
    ...     print(exp['month'], exp['experiments'])
    ...
    2015-06-01 00:00:00+10:00 1
    2016-01-01 00:00:00+11:00 1
    2014-06-01 00:00:00+10:00 1

#### `TimeField` truncation

class `TruncHour`(expression, output_field=None, tzinfo=None, **extra)
  `kind = 'hour'`

class `TruncMinute`(expression, output_field=None, tzinfo=None, **extra)
  `kind = 'minute'`

class `TruncSecond`(expression, output_field=None, tzinfo=None, **extra)
  `kind = 'second'`

These are logically equivalent to `Trunc('time_field', kind)`. They truncate all parts of the time up to `kind` which allows grouping or filtering times with less precision. `expression` can have an `output_field` of either `TimeField` or `DateTimeField`.

Since `TimeField`s don’t have a date component, only `Trunc` subclasses that deal with time-parts can be used with `TimeField`:

    >>> from datetime import datetime
    >>> from django.db.models import Count, TimeField
    >>> from django.db.models.functions import TruncHour
    >>> from django.utils import timezone
    >>> start1 = datetime(2014, 6, 15, 14, 30, 50, 321, tzinfo=timezone.utc)
    >>> start2 = datetime(2014, 6, 15, 14, 40, 2, 123, tzinfo=timezone.utc)
    >>> start3 = datetime(2015, 12, 31, 17, 5, 27, 999, tzinfo=timezone.utc)
    >>> Experiment.objects.create(start_datetime=start1, start_time=start1.time())
    >>> Experiment.objects.create(start_datetime=start2, start_time=start2.time())
    >>> Experiment.objects.create(start_datetime=start3, start_time=start3.time())
    >>> experiments_per_hour = Experiment.objects.annotate(
    ...    hour=TruncHour('start_datetime', output_field=TimeField()),
    ... ).values('hour').annotate(experiments=Count('id'))
    >>> for exp in experiments_per_hour:
    ...     print(exp['hour'], exp['experiments'])
    ...
    14:00:00 2
    17:00:00 1

    >>> import pytz
    >>> melb = pytz.timezone('Australia/Melbourne')
    >>> experiments_per_hour = Experiment.objects.annotate(
    ...    hour=TruncHour('start_datetime', tzinfo=melb),
    ... ).values('hour').annotate(experiments=Count('id'))
    >>> for exp in experiments_per_hour:
    ...     print(exp['hour'], exp['experiments'])
    ...
    2014-06-16 00:00:00+10:00 2
    2016-01-01 04:00:00+11:00 1

#### `DateTimeField` truncation

class `TruncDate`(expression, **extra)
  `lookup_name = 'date'`
  `output_field = DateField()`

`TruncDate` casts `expression` to a date rather than using the built-in SQL truncate function. It’s also registered as a transform on `DateTimeField` as `__date`.

class `TruncTime`(expression, **extra)

`lookup_name = 'time'`

`output_field = TimeField()`

`TruncTime` casts `expression` to a time rather than using the built-in SQL truncate function. It’s also registered as a transform on `DateTimeField` as `__time`.

class `TruncDay`(expression, output_field=None, tzinfo=None, **extra)
  `kind = 'day'`

class `TruncHour`(expression, output_field=None, tzinfo=None, **extra)
  `kind = 'hour'`

class `TruncMinute`(expression, output_field=None, tzinfo=None, **extra)
  `kind = 'minute'`

class `TruncSecond`(expression, output_field=None, tzinfo=None, **extra)
  `kind = 'second'`

These are logically equivalent to `Trunc('datetime_field', kind)`. They truncate all parts of the date up to `kind` and allow grouping or filtering datetimes with less precision. `expression` must have an `output_field` of `DateTimeField`.

Usage example:

    >>> from datetime import date, datetime
    >>> from django.db.models import Count
    >>> from django.db.models.functions import (
    ...     TruncDate, TruncDay, TruncHour, TruncMinute, TruncSecond,
    ... )
    >>> from django.utils import timezone
    >>> import pytz
    >>> start1 = datetime(2014, 6, 15, 14, 30, 50, 321, tzinfo=timezone.utc)
    >>> Experiment.objects.create(start_datetime=start1, start_date=start1.date())
    >>> melb = pytz.timezone('Australia/Melbourne')
    >>> Experiment.objects.annotate(
    ...     date=TruncDate('start_datetime'),
    ...     day=TruncDay('start_datetime', tzinfo=melb),
    ...     hour=TruncHour('start_datetime', tzinfo=melb),
    ...     minute=TruncMinute('start_datetime'),
    ...     second=TruncSecond('start_datetime'),
    ... ).values('date', 'day', 'hour', 'minute', 'second').get()
    {'date': datetime.date(2014, 6, 15),
     'day': datetime.datetime(2014, 6, 16, 0, 0, tzinfo=<DstTzInfo 'Australia/Melbourne' AEST+10:00:00 STD>),
     'hour': datetime.datetime(2014, 6, 16, 0, 0, tzinfo=<DstTzInfo 'Australia/Melbourne' AEST+10:00:00 STD>),
     'minute': 'minute': datetime.datetime(2014, 6, 15, 14, 30, tzinfo=<UTC>),
     'second': datetime.datetime(2014, 6, 15, 14, 30, 50, tzinfo=<UTC>)
    }